Cross-Functional Collaboration
Companies with AI teams comprising both technical and business roles will achieve higher value realisation, as we have seen with the adoption of new paradigms.
Sample assessment questions for each level:
- Level -1: “Is there active resistance to cross-functional collaboration for AI initiatives?”
- Level 0: “Does cross-functional collaboration happen informally without organisational structure?”
- Level 1: “Has the organisation identified benefits of cross-functional AI teams?”
- Level 2: “Are cross-functional teams formed for specific AI initiatives?”
- Level 3: “Do business and technical stakeholders collaborate effectively on AI in SDLC processes?”
- Level 4: “Is decision-making about AI transparent with input from diverse perspectives?”
- Level 5: “Are cross-functional AI teams the standard with integrated objectives and metrics?”
Key metrics to track:
- Cross-functional collaboration frequency: Number of joint AI-related initiatives
- Communication quality index: Clarity and effectiveness of AI-related communications
- Consensus decision-making: Time to reach decisions about AI implementation approaches
- Siloed knowledge assessment: Degree to which AI expertise is concentrated vs. distributed
- Business-IT alignment score: Measured through structured assessment tools
